Description

Apply advanced statistical concepts and machine learning to solve complex analytic problems within a federal environment.

Design and employ research methods for data collection and large-scale analysis. Build, train, test, and evaluate supervised and unsupervised analytic models using quantitative data. Clean and process large, real-world datasets to develop software tools, models, or reports. Retrieve and manipulate data from diverse sources including Db2, Oracle, SQL Server, Hadoop, and flat files. Communicate complex technical concepts to executive leadership and cross-functional teams.

Responsibilities

• Design and employ research methods for data collection and large-scale analysis.
• Build, train, test, and evaluate supervised and unsupervised analytic models.
• Clean and process large, real-world datasets to develop software tools and reports.
• Retrieve and manipulate data from Db2, Oracle, SQL Server, Hadoop, and flat files.
• Communicate complex technical concepts to executive leadership and cross-functional teams.

Required Skills

• 12+ years of experience in data science and predictive modeling.
• Expert-level proficiency in Python, R, and SAS.
• Advanced knowledge of Machine Learning and Gen AI.
• Deep experience with TensorFlow, PyTorch, scikit-learn, and NLTK.
• Strong database management skills using MySQL, SQLite, and SQL.
• Experience with Amazon Web Services EC2.
• Mandatory experience working with federal clients.

Preferred Skills

• Experience with anti-fraud applications in government or large private organizations.
• Knowledge of parallel processing, GPU programming with CUDA, or Mathematica.
• Proficiency in markup languages such as LaTeX and HTML.

Key Skills

Education

Any Gradute